Estimating monthly concentrations of ambient key air pollutants in Japan during 2010–2015 for a national-scale birth cohort. (1st September 2021)

• Record Type: Journal Article
• Authors: Araki, Shin; Hasunuma, Hideki; Yamamoto, Kouhei; Shima, Masayuki; Michikawa, Takehiro; Nitta, Hiroshi; Nakayama, Shoji F.; Yamazaki, Shin
• Is Part Of: Environmental pollution. Volume 284(2021)
• Publication Date: 2021-09-01
• Subjects: Random forests -- Machine learning -- Kriging -- Spatial distribution -- Exposure assessment; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2021.117483
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: Exposure to ambient air pollution is associated with maternal and child health. Some air pollutants exhibit similar behavior in the atmosphere, and some interact with each other; thus, comprehensive assessments of individual air pollutants are required. In this study, we developed national-scale monthly models for six air pollutants (NO, NO2, SO2, O3, PM2.5, and suspended particulate matter (SPM)) to obtain accurate estimates of pollutant concentrations at 1 km × 1 km resolution from 2010 through 2015 for application to the Japan Environment and Children's Study (JECS), which is a large-scale birth cohort study. We developed our models in the land use regression framework using random forests in conjunction with kriging. We evaluated the model performance via 5-fold location-based cross-validation. We successfully predicted monthly NO ( r 2 = 0.65), NO2 ( r 2 = 0.84), O3 ( r 2 = 0.86), PM2.5 ( r 2 = 0.79), and SPM ( r 2 = 0.64) concentrations. For SO2, a satisfactory model could not be developed ( r 2 = 0.45) because of the low SO2 concentrations in Japan. The performance of our models is comparable to those reported in previous studies at similar temporal and spatial scales. The model predictions in conjunction with the JECS will reveal the critical windows of prenatal and infancy exposure to ambient air pollutants, thus contributing to the development of environmental policies on air pollution. Graphical abstract: Image 1 Highlights: National-scale monthly exposure models were built for six ambient key air pollutants. Random forests in conjunction with kriging on the regression residuals were used. We achieved accurate NO, NO2, O3, PM2.5, and suspended particulate matter estimates. Monthly estimates nationwide were obtained from 2010 to 2015 at 1 km resolution. The estimates were obtained to be applied to a national-scale birth cohort in Japan.